Seasonal and interannual variability of oceanographic conditions in a Northeast Greenland Fjord
Bibliographic record
Abstract
The Arctic is undergoing rapid changes due to climatic changes. Studies show that the Arctic is not only warming, but also freshening, which can induce changes to the distribution and spreading pathways of freshwater and impact ecosystems. Here, we focus on the coast of Northeast Greenland, which lies along the primary outflow shelf of the Arctic Ocean. Long term mooring-arrays monitor the gateways of the East Greenland Current at Fram Strait and Denmark Strait, but seasonal and interannual variability of oceanographic conditions along the coast of Northeast Greenland and its impact on fjord hydrography are not well known. This is mainly due to costs and logistical constraints encountered when operating in such a harsh and remote environment, where sea ice hampers coastal navigation. For this thesis, we analyzed in-situ observations, including moorings, from Young Sound-Tyrolerfjord (74° N), to gain more knowledge on the seasonal and long-term response of the fjord system to local and regional processes inducing changes in oceanographic conditions in the fjord and in the coastal domain. Our results include a description of the variability in hydrography and circulation during the ice-covered period, an impact analysis of coastal freshening on the renewal of the fjord basin water, and a process study of the drivers of freshwater variability along the coast of Northeast Greenland. The results suggest that sea ice melt along the coast is a prominent driver of freshwater variability in the coastal domain, and that sea ice melt might be impacted by the recirculation of warm Atlantic Water. An increase of temperatures in the North Atlantic could induce more sea ice might melt at higher latitude and freshen the coastal waters of Northeast Greenland. This is important, as our data already shows that after strong costal freshening in the periods since 2005, fjord bottom renewal of Young Sound-Tyrolerfjord was prevented, which may affect the fjords ecosystem functions. This study was enabled by the extensive dataset from the Marin Basis Monitoring Program under the Greenland Ecosystem Monitoring Program, and underlines the importance to maintain strong monitoring capacity in Northeast Greenland, to asses recent and future changes to the marine system due to climate change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".